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Metatranscriptome analysis reveals host-microbiome interactions in traps of carnivorous Genlisea species.

ABSTRACT: In the carnivorous plant genus Genlisea a unique lobster pot trapping mechanism supplements nutrition in nutrient-poor habitats. A wide spectrum of microbes frequently occurs in Genlisea's leaf-derived traps without clear relevance for Genlisea carnivory. We sequenced the metatranscriptomes of subterrestrial traps vs. the aerial chlorophyll-containing leaves of G. nigrocaulis and of G. hispidula. Ribosomal RNA assignment revealed soil-borne microbial diversity in Genlisea traps, with 92 genera of 19 phyla present in more than one sample. Microbes from 16 of these phyla including proteobacteria, green algae, amoebozoa, fungi, ciliates and metazoans, contributed additionally short-lived mRNA to the metatranscriptome. Furthermore, transcripts of 438 members of hydrolases (e.g., proteases, phosphatases, lipases), mainly resembling those of metazoans, ciliates and green algae, were found. Compared to aerial leaves, Genlisea traps displayed a transcriptional up-regulation of endogenous NADH oxidases generating reactive oxygen species as well as of acid phosphatases for prey digestion. A leaf-vs.-trap transcriptome comparison reflects that carnivory provides inorganic P- and different forms of N-compounds (ammonium, nitrate, amino acid, oligopeptides) and implies the need to protect trap cells against oxidative stress. The analysis elucidates a complex food web inside the Genlisea traps, and suggests ecological relationships between this plant genus and its entrapped microbiome.

SUBMITTER: Cao HX

PROVIDER: S-EPMC4500957 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Metatranscriptome analysis reveals host-microbiome interactions in traps of carnivorous Genlisea species.

Cao Hieu X HX Schmutzer Thomas T Scholz Uwe U Pecinka Ales A Schubert Ingo I Vu Giang T H GT

Frontiers in microbiology 20150714

In the carnivorous plant genus Genlisea a unique lobster pot trapping mechanism supplements nutrition in nutrient-poor habitats. A wide spectrum of microbes frequently occurs in Genlisea's leaf-derived traps without clear relevance for Genlisea carnivory. We sequenced the metatranscriptomes of subterrestrial traps vs. the aerial chlorophyll-containing leaves of G. nigrocaulis and of G. hispidula. Ribosomal RNA assignment revealed soil-borne microbial diversity in Genlisea traps, with 92 genera o ...[more]

PMID: 26236284

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Project description:BACKGROUND:Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases. Extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery. METHODS:Through a multi-institutional collaboration, a community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the Open Biological/Biomedical Ontologies (OBO) Foundry principles. As an OBO library ontology, OHMI leverages established ontologies to create logically structured representations of (1) microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and (2) associated study protocols and types of data analysis and experimental results. RESULTS:Aligned with the Basic Formal Ontology, OHMI comprises over 1000 terms, including terms imported from more than 10 existing ontologies together with some 500 OHMI-specific terms. A specific OHMI design pattern was generated to represent typical host-microbiome interaction studies. As one major OHMI use case, drawing on data from over 50 peer-reviewed publications, we identified over 100 bacteria and fungi from the gut, oral cavity, skin, and airway that are associated with six rheumatic diseases including rheumatoid arthritis. Our ontological study identified new high-level microbiota taxonomical structures. Two microbiome-related competency questions were also designed and addressed. We were also able to use OHMI to represent statistically significant results identified from a large existing microbiome database data analysis. CONCLUSION:OHMI represents entities and relations in the domain of HMIs. It supports shared knowledge representation, data and metadata standardization and integration, and can be used in formulation of advanced queries for purposes of data analysis.

Dataset Information

Metatranscriptome analysis reveals host-microbiome interactions in traps of carnivorous Genlisea species.

Publications

Metatranscriptome analysis reveals host-microbiome interactions in traps of carnivorous Genlisea species.

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